Selected Lecture Notes

Introduction to Computational Mathematics
Section 5: Matrix Norms, Inequalities, and Conditioning
Section 6: Least Squares and Householder Transformations
Section 7: Fixed Point and Newton's Method
Section 8: Finite Differences and Lagrange Interpolation
Section 10: IVPs and Euler's Method
Section 11: Runge Kutta Methods
Linear Algebra Review Sessions
Linear Algebra Review Session 1 (part 1)
Linear Algebra Review Session 1 (part 2)
Linear Algebra Review Session 2
Directed Reading Program
Why Does Gradient Descent Work (well)?

Course Roster

Developed
Data Analytics Workshop (AS.110.100) Spring 2023
College Algebra (collaborator, AS.110.102) Summer 2021
Taught
Data Analytics Workshop (AS.110.100) Summer 2023, 2024, 2025, 2026
Graduate TA
Machine Learning 1 (EN.553.740) Fall 2025
Introduction to Computational Mathematics (EN.553.385) Spring 2025, Spring 2026
Introduction to Convexity (EN.553.665) Spring 2024, Fall 2024
Matrix Analysis and Linear Algebra (EN.553.792) Fall 2023
Mathematical Game Theory (EN.553.653) Spring 2023
Mathematical Modeling and Consulting (EN.553.400) Spring 2023
Optimization in Finance (EN.553.661) Fall 2022
Undergraduate TA
Real Analysis I (EN.553.405) Spring 2022, Summer 2022
Cryptology and Coding (EN.553.371) Spring 2022
Calculus II (For Biological and Social Science) (AS.110.107) Spring 2022
Honors Discrete Mathematics (EN.553.172) Fall 2021
Differential Equations and Applications (AS.110.302) Fall 2021, Spring 2021
Discrete Mathematics (EN.553.171) Spring 2021, Fall 2020
Calculus III (AS.110.202) Fall 2020
Introduction to Computing (AS.205.205) Spring 2020